The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for producing quantitative measurements related to adipose tissue using MRI.
Metabolic syndrome is a “clustering” of metabolic abnormalities and cardiovascular risk factors, including obesity, type II diabetes, fatty liver disease and coronary artery disease. People suffering from metabolic syndrome are three times more likely to have a heart attack or stroke, have five-fold greater risk of type II diabetes, and have increased rates of cardiovascular disease and premature death. While the underlying causes of metabolic syndrome are not fully understood, central obesity indicated by excessive visceral adipose tissue (“VAT”) inside the abdomen, is known to be a dominant risk factor. In other words, both the amount and the distribution of abdominal fat determine the risk for metabolic syndrome; therefore, any biomarker for central obesity should provide information about both the amount and distribution of abdominal fat to be effective. Ideally, measurement of central obesity should have a direct physiological basis for maximal clinical relevance, requiring a quantitative technique that is independent of platform and protocol.
Unfortunately, no clinical consensus currently exists on diagnostic criteria for central obesity, which severely hinders prospective diagnosis, treatment monitoring, and epidemiological studies of the disease. Anthropometric biomarkers for central obesity such as waist circumference, waist-hip ratio, and body mass index (“BMI”) are widely used in the clinical setting; however, these anthropometric measures are not direct physiological measurements of central obesity, but rather indirect surrogates that fail to accurately measure VAT volume. Anthropometric measures are also highly prone to systematic error due to methodological variability in anatomic site, respiratory phase, and even meal timings.
Direct measurement of VAT volume using diagnostic imaging techniques is preferable to anthropometric surrogates, and satisfies the requirement of a physiological basis. For example, x-ray computed tomography (“CT”) can provide full abdominal and pelvic coverage with acquisition times of only a few seconds. Unfortunately, CT exposes the patient to medically unnecessary doses of ionizing radiation, limiting its clinical use to diagnosing acute patient illnesses. A safe alternative is T1-weighted magnetic resonance imaging (“MRI”), which delivers no ionizing radiation dose. However, both CT and T1-weighted MRI require hours of prohibitively tedious manual segmentation of VAT from subcutaneous adipose tissue and non-adipose tissues, a process that is cost-inefficient and highly prone to systematic error. Alternatively, histogram-based semi-automatic thresholding of T1-weighted images can be used to identify adipose tissue, but such methods are purely qualitative due to partial volume effects and signal inhomogeneities and, thus, do not provide quantitative measures of VAT.
Adipose tissue segmentation is considerably more efficient and accurate if the fat signal can be isolated during image acquisition. Among techniques for direct imaging of fat, chemical-shift-based MRI has been shown to have superior fat-water separation quality. These techniques exploit the resonance frequency difference between fat and water to provide separate, co-registered images of water, fat and “fat-fraction.” In principle, these chemical-shift fat-water imaging methods have great potential for automated adipose tissue segmentation because adipose tissue may be rapidly separated from non-adipose tissue using only a simple fat-fraction threshold, which is typically fifty percent. The time efficiency of using fat-fraction values to segment adipose tissue is a major advantage of chemical-shift methods over manual segmentation; however, prior to thresholding, fat-fraction maps require empirical masking to remove noise in background areas, air cavities, and signal voids, which partly negates the speed advantage of these techniques.
Complete anatomical coverage of the abdomen and pelvis is also necessary to characterize the entire VAT volume. Even using fast three-dimensional gradient-echo sequences and parallel imaging, this is a challenging data acquisition constraint, requiring either multiple breath-hold acquisitions or coarse spatial resolution. Acquiring low-resolution data permits whole-body adipose tissue characterization, but the accuracy of adipose tissue volume measurement is undermined by partial-volume effects. Multiple breath-hold acquisitions allow for higher resolution data, but are more vulnerable to motion artifacts, and may also require corrections for image misregistration between acquisitions.
Furthermore, the accuracy of chemical shift methods is confounded by a number of physical factors including T1 and T2* relaxation effects and fat spectral complexity, which if left uncorrected will result in large and significant errors in fat-fraction values. Since most studies define adipose tissue as having fat-fraction values of fifty percent or higher, these errors directly impact the accuracy of VAT or total adipose tissue (“TAT”) volume estimation. A chemical-shift fat-water technique that can correct for all confounding factors in fat-fraction measurement is therefore an absolute requirement for truly quantitative adipose tissue measurements.
It would therefore be desirable to provide an accurate, reliable, and generalized system and method for producing quantitative measurements related to adipose tissue.